{"title":"基于广义析取规划法的电动客车运行非线性模型预测控制","authors":"Yin Yuan;Shukai Li;Chengpu Yu;Lixing Yang;Ziyou Gao","doi":"10.1109/TCST.2025.3560220","DOIUrl":null,"url":null,"abstract":"This article investigates the nonlinear model predictive control (NMPC) for electric bus operations (EBOs) under dynamic environments, based on the generalized disjunctive programming (GDP) method. Specifically, we construct discrete-event model to capture the dynamic of bus traffic, passenger load, and current electricity. With the safety constraints, we incorporate algebraic equations, disjunctions, and logical propositions to formulate a nonconvex GDP model, for the nonlinear optimal control problem with both discrete and continuous components. Tailored to the nonlinearity and disjunctions, we design a GDP-based branch and bound (GDPB) algorithm with domain reduction under the model prediction control scheme. The main idea entails branching on constraints regarding disjunctive terms and spatial disjunctions, to convert the complex original problem with discrete and continuous variables as well as nonlinear and nonconvex constraints and cost functions into quadratic programming (QP) subproblems with reduced domains. It can ensure the rapid attainment of exact solutions for embedded applications. Extensive experiments confirm the effectiveness of the proposed control (PC) method. Additionally, the solution algorithm demonstrates desirable computational efficiency, suitable for online implementations.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"33 5","pages":"1820-1834"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nonlinear Model Predictive Control for Electric Bus Operations Based on Generalized Disjunctive Programming Method\",\"authors\":\"Yin Yuan;Shukai Li;Chengpu Yu;Lixing Yang;Ziyou Gao\",\"doi\":\"10.1109/TCST.2025.3560220\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article investigates the nonlinear model predictive control (NMPC) for electric bus operations (EBOs) under dynamic environments, based on the generalized disjunctive programming (GDP) method. Specifically, we construct discrete-event model to capture the dynamic of bus traffic, passenger load, and current electricity. With the safety constraints, we incorporate algebraic equations, disjunctions, and logical propositions to formulate a nonconvex GDP model, for the nonlinear optimal control problem with both discrete and continuous components. Tailored to the nonlinearity and disjunctions, we design a GDP-based branch and bound (GDPB) algorithm with domain reduction under the model prediction control scheme. The main idea entails branching on constraints regarding disjunctive terms and spatial disjunctions, to convert the complex original problem with discrete and continuous variables as well as nonlinear and nonconvex constraints and cost functions into quadratic programming (QP) subproblems with reduced domains. It can ensure the rapid attainment of exact solutions for embedded applications. Extensive experiments confirm the effectiveness of the proposed control (PC) method. Additionally, the solution algorithm demonstrates desirable computational efficiency, suitable for online implementations.\",\"PeriodicalId\":13103,\"journal\":{\"name\":\"IEEE Transactions on Control Systems Technology\",\"volume\":\"33 5\",\"pages\":\"1820-1834\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-03-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Control Systems Technology\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11003154/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Control Systems Technology","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11003154/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Nonlinear Model Predictive Control for Electric Bus Operations Based on Generalized Disjunctive Programming Method
This article investigates the nonlinear model predictive control (NMPC) for electric bus operations (EBOs) under dynamic environments, based on the generalized disjunctive programming (GDP) method. Specifically, we construct discrete-event model to capture the dynamic of bus traffic, passenger load, and current electricity. With the safety constraints, we incorporate algebraic equations, disjunctions, and logical propositions to formulate a nonconvex GDP model, for the nonlinear optimal control problem with both discrete and continuous components. Tailored to the nonlinearity and disjunctions, we design a GDP-based branch and bound (GDPB) algorithm with domain reduction under the model prediction control scheme. The main idea entails branching on constraints regarding disjunctive terms and spatial disjunctions, to convert the complex original problem with discrete and continuous variables as well as nonlinear and nonconvex constraints and cost functions into quadratic programming (QP) subproblems with reduced domains. It can ensure the rapid attainment of exact solutions for embedded applications. Extensive experiments confirm the effectiveness of the proposed control (PC) method. Additionally, the solution algorithm demonstrates desirable computational efficiency, suitable for online implementations.
期刊介绍:
The IEEE Transactions on Control Systems Technology publishes high quality technical papers on technological advances in control engineering. The word technology is from the Greek technologia. The modern meaning is a scientific method to achieve a practical purpose. Control Systems Technology includes all aspects of control engineering needed to implement practical control systems, from analysis and design, through simulation and hardware. A primary purpose of the IEEE Transactions on Control Systems Technology is to have an archival publication which will bridge the gap between theory and practice. Papers are published in the IEEE Transactions on Control System Technology which disclose significant new knowledge, exploratory developments, or practical applications in all aspects of technology needed to implement control systems, from analysis and design through simulation, and hardware.